Question

A healthcare analytics team wants to use a large corpus of clinician free-text notes to build a research dataset. The structured fields (name, MRN, date of birth) are easily tokenized, but the notes themselves contain embedded patient names, phone numbers, and addresses written inline by clinicians. A privacy engineer is asked to design a technical control so the notes can be shared with researchers with minimal re-identification risk. Which approach best addresses the privacy risk in the unstructured free-text?

Accepted Answer

Apply automated named-entity recognition (NER) to detect and redact direct identifiers in the free text, followed by human quality review of a risk-based sample before release

Answer

Encrypt the entire notes field at rest with a field-level key and grant researchers decryption access under a data use agreement

Answer

Tokenize the structured identifier fields and release the free-text notes unchanged, relying on the researchers' contractual confidentiality obligations

Answer

Hash the notes field with a salted SHA-256 function so the original identifiers cannot be recovered from the shared dataset